Term-level queries
You can use term-level queries to find documents based on precise values in structured data. Examples of structured data include date ranges, IP addresses, prices, or product IDs.
Unlike full-text queries, term-level queries do not analyze search terms. Instead, term-level queries match the exact terms stored in a field.
|
Note
|
Term-level queries still normalize search terms for |
Types of term-level queries
exists
query-
Returns documents that contain any indexed value for a field.
fuzzy
query-
Returns documents that contain terms similar to the search term. OpenSearch measures similarity, or fuzziness, using a Levenshtein edit distance.
ids
query-
Returns documents based on their document IDs.
prefix
query-
Returns documents that contain a specific prefix in a provided field.
range
query-
Returns documents that contain terms within a provided range.
regexp
query-
Returns documents that contain terms matching a regular expression.
term
query-
Returns documents that contain an exact term in a provided field.
terms
query-
Returns documents that contain one or more exact terms in a provided field.
terms_set
query-
Returns documents that contain a minimum number of exact terms in a provided field. You can define the minimum number of matching terms using a field or script.
type
query-
Returns documents of the specified type.
wildcard
query-
Returns documents that contain terms matching a wildcard pattern.
Exists query
Returns documents that contain an indexed value for a field.
An indexed value may not exist for a document’s field due to a variety of reasons:
-
The field in the source JSON is
null
or[]
-
The field has
"index" : false
set in the mapping -
The length of the field value exceeded an
ignore_above
setting in the mapping -
The field value was malformed and
ignore_malformed
was defined in the mapping
Example request
GET /_search
{
"query": {
"exists": {
"field": "user"
}
}
}
Top-level parameters for exists
field
-
(Required, string) Name of the field you wish to search.
While a field is deemed non-existent if the JSON value is
null
or[]
, these values will indicate the field does exist:-
Empty strings, such as
""
or"-"
-
Arrays containing
null
and another value, such as[null, "foo"]
-
A custom
null-value
, defined in field mapping
-
Notes
Find documents missing indexed values
To find documents that are missing an indexed value for a field,
use the must_not
boolean query with the exists
query.
The following search returns documents that are missing an indexed value for
the user.id
field.
GET /_search
{
"query": {
"bool": {
"must_not": {
"exists": {
"field": "user.id"
}
}
}
}
}
Fuzzy query
Returns documents that contain terms similar to the search term, as measured by a Levenshtein edit distance.
An edit distance is the number of one-character changes needed to turn one term into another. These changes can include:
-
Changing a character (box → fox)
-
Removing a character (black → lack)
-
Inserting a character (sic → sick)
-
Transposing two adjacent characters (act → cat)
To find similar terms, the fuzzy
query creates a set of all possible
variations, or expansions, of the search term within a specified edit distance.
The query then returns exact matches for each expansion.
Example requests
Simple example
GET /_search
{
"query": {
"fuzzy": {
"user.id": {
"value": "ki"
}
}
}
}
Example using advanced parameters
GET /_search
{
"query": {
"fuzzy": {
"user.id": {
"value": "ki",
"fuzziness": "AUTO",
"max_expansions": 50,
"prefix_length": 0,
"transpositions": true,
"rewrite": "constant_score"
}
}
}
}
Top-level parameters for fuzzy
<field>
-
(Required, object) Field you wish to search.
Parameters for <field>
value
-
(Required, string) Term you wish to find in the provided
<field>
. fuzziness
-
(Optional, string) Maximum edit distance allowed for matching. See Fuzziness for valid values and more information.
max_expansions
-
(Optional, integer) Maximum number of variations created. Defaults to
50
.WarningAvoid using a high value in the max_expansions
parameter, especially if theprefix_length
parameter value is0
. High values in themax_expansions
parameter can cause poor performance due to the high number of variations examined. prefix_length
-
(Optional, integer) Number of beginning characters left unchanged when creating expansions. Defaults to
0
. transpositions
-
(Optional, Boolean) Indicates whether edits include transpositions of two adjacent characters (ab → ba). Defaults to
true
. rewrite
-
(Optional, string) Method used to rewrite the query. For valid values and more information, see the
rewrite
parameter.
Notes
Fuzzy queries will not be executed if search.allow_expensive_queries
is set to false.
IDs
Returns documents based on their IDs. This query uses document IDs stored in
the _id
field.
Example request
GET /_search
{
"query": {
"ids" : {
"values" : ["1", "4", "100"]
}
}
}
Top-level parameters for ids
values
-
(Required, array of strings) An array of document IDs.
Prefix query
Returns documents that contain a specific prefix in a provided field.
Example request
The following search returns documents where the user.id
field contains a term
that begins with ki
.
GET /_search
{
"query": {
"prefix": {
"user.id": {
"value": "ki"
}
}
}
}
Top-level parameters for prefix
<field>
-
(Required, object) Field you wish to search.
Parameters for <field>
value
-
(Required, string) Beginning characters of terms you wish to find in the provided
<field>
. rewrite
-
(Optional, string) Method used to rewrite the query. For valid values and more information, see the
rewrite
parameter. case_insensitive
-
(Optional, Boolean) allows ASCII case insensitive matching of the value with the indexed field values when set to true. Default is false which means the case sensitivity of matching depends on the underlying field’s mapping.
Notes
Short request example
You can simplify the prefix
query syntax by combining the <field>
and
value
parameters. For example:
GET /_search
{
"query": {
"prefix" : { "user" : "ki" }
}
}
Speed up prefix queries
You can speed up prefix queries using the index_prefixes
mapping parameter. If enabled, OpenSearch indexes prefixes between 2 and 5
characters in a separate field. This lets OpenSearch run prefix queries more
efficiently at the cost of a larger index.
Allow expensive queries
Prefix queries will not be executed if search.allow_expensive_queries
is set to false. However, if index_prefixes
are enabled, an optimised query is built which
is not considered slow, and will be executed in spite of this setting.
Range query
Returns documents that contain terms within a provided range.
Example request
The following search returns documents where the age
field contains a term
between 10
and 20
.
GET /_search
{
"query": {
"range": {
"age": {
"gte": 10,
"lte": 20,
"boost": 2.0
}
}
}
}
Top-level parameters for range
<field>
-
(Required, object) Field you wish to search.
Parameters for <field>
gt
-
(Optional) Greater than.
gte
-
(Optional) Greater than or equal to.
lt
-
(Optional) Less than.
lte
-
(Optional) Less than or equal to.
format
-
(Optional, string) Date format used to convert
date
values in the query.By default, OpenSearch uses the date
format
provided in the `<field>’s mapping. This value overrides that mapping format.For valid syntax, see
format
.WarningIf a format or date value is incomplete, the range query replaces any missing components with default values. See Missing date components.
relation
-
(Optional, string) Indicates how the range query matches values for
range
fields. Valid values are:INTERSECTS
(Default)-
Matches documents with a range field value that intersects the query’s range.
CONTAINS
-
Matches documents with a range field value that entirely contains the query’s range.
WITHIN
-
Matches documents with a range field value entirely within the query’s range.
time_zone
-
(Optional, string) Coordinated Universal Time (UTC) offset or IANA time zone used to convert
date
values in the query to UTC.Valid values are ISO 8601 UTC offsets, such as
+01:00
or -08:00
, and IANA time zone IDs, such asAmerica/Los_Angeles
.For an example query using the
time_zone
parameter, see Time zone inrange
queries.NoteThe
time_zone
parameter does not affect the date math value ofnow
.now
is always the current system time in UTC.However, the
time_zone
parameter does convert dates calculated usingnow
and date math rounding. For example, thetime_zone
parameter will convert a value ofnow/d
. boost
-
(Optional, float) Floating point number used to decrease or increase the relevance scores of a query. Defaults to
1.0
.You can use the
boost
parameter to adjust relevance scores for searches containing two or more queries.Boost values are relative to the default value of
1.0
. A boost value between0
and1.0
decreases the relevance score. A value greater than1.0
increases the relevance score.
Notes
Using the range
query with text
and keyword
fields
Range queries on text
or keyword
fields will not be executed if
search.allow_expensive_queries
is set to false.
Using the range
query with date
fields
When the <field>
parameter is a date
field data type, you can use
date math with the following parameters:
-
gt
-
gte
-
lt
-
lte
For example, the following search returns documents where the timestamp
field
contains a date between today and yesterday.
GET /_search
{
"query": {
"range": {
"timestamp": {
"gte": "now-1d/d",
"lt": "now/d"
}
}
}
}
Missing date components
For range queries and date range aggregations, OpenSearch replaces missing date components with the following values. Missing year components are not replaced.
MONTH_OF_YEAR: 01
DAY_OF_MONTH: 01
HOUR_OF_DAY: 23
MINUTE_OF_HOUR: 59
SECOND_OF_MINUTE: 59
NANO_OF_SECOND: 999_999_999
For example, if the format is yyyy-MM
, OpenSearch converts a gt
value of 2099-12
to 2099-12-01T23:59:59.999_999_999Z
. This date uses the provided year (2099
)
and month (12
) but uses the default day (01
), hour (23
), minute (59
),
second (59
), and nanosecond (999_999_999
).
Date math and rounding
OpenSearch rounds date math values in parameters as follows:
gt
-
Rounds up to the first millisecond not covered by the rounded date.
For example,
2014-11-18||/M
rounds up to2014-12-01T00:00:00.000
, excluding the entire month of November. gte
-
Rounds down to the first millisecond.
For example,
2014-11-18||/M
rounds down to2014-11-01T00:00:00.000
, including the entire month. lt
-
Rounds down to the last millisecond before the rounded value.
For example,
2014-11-18||/M
rounds down to2014-10-31T23:59:59.999
, excluding the entire month of November. lte
-
Rounds up to the latest millisecond in the rounding interval.
For example,
2014-11-18||/M
rounds up to2014-11-30T23:59:59.999
, including the entire month.
Example query using time_zone
parameter
You can use the time_zone
parameter to convert date
values to UTC using a
UTC offset. For example:
GET /_search
{
"query": {
"range": {
"timestamp": {
"time_zone": "+01:00", (1)
"gte": "2020-01-01T00:00:00", (2)
"lte": "now" (3)
}
}
}
}
-
Indicates that
date
values use a UTC offset of+01:00
. -
With a UTC offset of
+01:00
, OpenSearch converts this date to2019-12-31T23:00:00 UTC
. -
The
time_zone
parameter does not affect thenow
value.
Regexp query
Returns documents that contain terms matching a regular expression.
A regular expression is a way to match patterns in data using placeholder
characters, called operators. For a list of operators supported by the
regexp
query, see Regular expression syntax.
Example request
The following search returns documents where the user.id
field contains any term
that begins with b
and ends with o
. The .*
operators match any
characters of any length, including no characters. Matching
terms can include bo
, bio
, and bilbo
.
GET /_search
{
"query": {
"regexp": {
"user.id": {
"value": "b.*o",
"flags": "ALL",
"case_insensitive": true,
"max_determinized_states": 10000,
"rewrite": "constant_score"
}
}
}
}
Top-level parameters for regexp
<field>
-
(Required, object) Field you wish to search.
Parameters for <field>
value
-
(Required, string) Regular expression for terms you wish to find in the provided
<field>
. For a list of supported operators, see Regular expression syntax.By default, regular expressions are limited to 1,000 characters. You can change this limit using the
index.max_regex_length
setting.WarningThe performance of the
regexp
query can vary based on the regular expression provided. To improve performance, avoid using wildcard patterns, such as.
or.?+
, without a prefix or suffix. flags
-
(Optional, string) Enables optional operators for the regular expression. For valid values and more information, see Regular expression syntax.
case_insensitive
-
(Optional, Boolean) allows case insensitive matching of the regular expression value with the indexed field values when set to true. Default is false which means the case sensitivity of matching depends on the underlying field’s mapping.
max_determinized_states
-
(Optional, integer) Maximum number of automaton states required for the query. Default is
10000
.OpenSearch uses Apache Lucene internally to parse regular expressions. Lucene converts each regular expression to a finite automaton containing a number of determinized states.
You can use this parameter to prevent that conversion from unintentionally consuming too many resources. You may need to increase this limit to run complex regular expressions.
rewrite
-
(Optional, string) Method used to rewrite the query. For valid values and more information, see the
rewrite
parameter.
Notes
Allow expensive queries
Regexp queries will not be executed if search.allow_expensive_queries
is set to false.
Term query
Returns documents that contain an exact term in a provided field.
You can use the term
query to find documents based on a precise value such as
a price, a product ID, or a username.
|
Warning
|
Avoid using the By default, OpenSearch changes the values of To search |
Example request
GET /_search
{
"query": {
"term": {
"user.id": {
"value": "bilbo",
"boost": 1.0
}
}
}
}
Top-level parameters for term
<field>
-
(Required, object) Field you wish to search.
Parameters for <field>
value
-
(Required, string) Term you wish to find in the provided
<field>
. To return a document, the term must exactly match the field value, including whitespace and capitalization. boost
-
(Optional, float) Floating point number used to decrease or increase the relevance scores of a query. Defaults to
1.0
.You can use the
boost
parameter to adjust relevance scores for searches containing two or more queries.Boost values are relative to the default value of
1.0
. A boost value between0
and1.0
decreases the relevance score. A value greater than1.0
increases the relevance score. case_insensitive
-
(Optional, Boolean) allows ASCII case insensitive matching of the value with the indexed field values when set to true. Default is false which means the case sensitivity of matching depends on the underlying field’s mapping
Notes
Avoid using the term
query for text
fields
By default, OpenSearch changes the values of text
fields during analysis. For
example, the default standard analyzer changes
text
field values as follows:
-
Removes most punctuation
-
Divides the remaining content into individual words, called tokens
-
Lowercases the tokens
To better search text
fields, the match
query also analyzes your provided
search term before performing a search. This means the match
query can search
text
fields for analyzed tokens rather than an exact term.
The term
query does not analyze the search term. The term
query only
searches for the exact term you provide. This means the term
query may
return poor or no results when searching text
fields.
To see the difference in search results, try the following example.
-
Create an index with a
text
field calledfull_text
.PUT my-index-000001 { "mappings": { "properties": { "full_text": { "type": "text" } } } }
-
Index a document with a value of
Quick Brown Foxes!
in thefull_text
field.PUT my-index-000001/_doc/1 { "full_text": "Quick Brown Foxes!" }
Because
full_text
is atext
field, OpenSearch changesQuick Brown Foxes!
to[quick, brown, fox]
during analysis. -
Use the
term
query to search forQuick Brown Foxes!
in thefull_text
field. Include thepretty
parameter so the response is more readable.GET my-index-000001/_search?pretty { "query": { "term": { "full_text": "Quick Brown Foxes!" } } }
Because the
full_text
field no longer contains the exact termQuick Brown Foxes!
, theterm
query search returns no results. -
Use the
match
query to search forQuick Brown Foxes!
in thefull_text
field.GET my-index-000001/_search?pretty { "query": { "match": { "full_text": "Quick Brown Foxes!" } } }
Unlike the
term
query, thematch
query analyzes your provided search term,Quick Brown Foxes!
, before performing a search. Thematch
query then returns any documents containing thequick
,brown
, orfox
tokens in thefull_text
field.Here’s the response for the
match
query search containing the indexed document in the results.{ "took" : 1, "timed_out" : false, "_shards" : { "total" : 1, "successful" : 1, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : { "value" : 1, "relation" : "eq" }, "max_score" : 0.8630463, "hits" : [ { "_index" : "my-index-000001", "_type" : "_doc", "_id" : "1", "_score" : 0.8630463, "_source" : { "full_text" : "Quick Brown Foxes!" } } ] } }
Terms query
Returns documents that contain one or more exact terms in a provided field.
The terms
query is the same as the term
query,
except you can search for multiple values.
Example request
The following search returns documents where the user.id
field contains bilbo
or elkbee
.
GET /_search
{
"query": {
"terms": {
"user.id": [ "bilbo", "elkbee" ],
"boost": 1.0
}
}
}
Top-level parameters for terms
<field>
-
(Optional, object) Field you wish to search.
The value of this parameter is an array of terms you wish to find in the provided field. To return a document, one or more terms must exactly match a field value, including whitespace and capitalization.
By default, OpenSearch limits the
terms
query to a maximum of 65,536 terms. You can change this limit using theindex.max_terms_count
setting.NoteTo use the field values of an existing document as search terms, use the terms lookup parameters. boost
-
(Optional, float) Floating point number used to decrease or increase the relevance scores of a query. Defaults to
1.0
.You can use the
boost
parameter to adjust relevance scores for searches containing two or more queries.Boost values are relative to the default value of
1.0
. A boost value between0
and1.0
decreases the relevance score. A value greater than1.0
increases the relevance score.
Notes
Highlighting terms
queries
Highlighting is best-effort only. OpenSearch may not
return highlight results for terms
queries depending on:
-
Highlighter type
-
Number of terms in the query
Terms lookup
Terms lookup fetches the field values of an existing document. OpenSearch then uses those values as search terms. This can be helpful when searching for a large set of terms.
Because terms lookup fetches values from a document, the _source
mapping field must be enabled to use terms lookup. The _source
field is enabled by default.
|
Note
|
By default, OpenSearch limits the terms query to a maximum of 65,536
terms. This includes terms fetched using terms lookup. You can change
this limit using the index.max_terms_count setting.
|
To perform a terms lookup, use the following parameters.
Terms lookup parameters
index
-
(Required, string) Name of the index from which to fetch field values.
id
-
(Required, string) ID of the document from which to fetch field values.
path
-
(Required, string) Name of the field from which to fetch field values. OpenSearch uses these values as search terms for the query.
If the field values include an array of nested inner objects, you can access those objects using dot notation syntax.
routing
-
(Optional, string) Custom routing value of the document from which to fetch term values. If a custom routing value was provided when the document was indexed, this parameter is required.
Terms lookup example
To see how terms lookup works, try the following example.
-
Create an index with a
keyword
field namedcolor
.PUT my-index-000001 { "mappings": { "properties": { "color": { "type": "keyword" } } } }
-
Index a document with an ID of 1 and values of
["blue", "green"]
in thecolor
field.PUT my-index-000001/_doc/1 { "color": ["blue", "green"] }
-
Index another document with an ID of 2 and value of
blue
in thecolor
field.PUT my-index-000001/_doc/2 { "color": "blue" }
-
Use the
terms
query with terms lookup parameters to find documents containing one or more of the same terms as document 2. Include thepretty
parameter so the response is more readable.GET my-index-000001/_search?pretty { "query": { "terms": { "color" : { "index" : "my-index-000001", "id" : "2", "path" : "color" } } } }
Because document 2 and document 1 both contain
blue
as a value in thecolor
field, OpenSearch returns both documents.{ "took" : 17, "timed_out" : false, "_shards" : { "total" : 1, "successful" : 1, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : { "value" : 2, "relation" : "eq" }, "max_score" : 1.0, "hits" : [ { "_index" : "my-index-000001", "_type" : "_doc", "_id" : "1", "_score" : 1.0, "_source" : { "color" : [ "blue", "green" ] } }, { "_index" : "my-index-000001", "_type" : "_doc", "_id" : "2", "_score" : 1.0, "_source" : { "color" : "blue" } } ] } }
Terms set query
Returns documents that contain a minimum number of exact terms in a provided field.
The terms_set
query is the same as the terms
query, except you can define the number of matching terms required to
return a document. For example:
-
A field,
programming_languages
, contains a list of known programming languages, such asc++
,java
, orphp
for job candidates. You can use theterms_set
query to return documents that match at least two of these languages. -
A field,
permissions
, contains a list of possible user permissions for an application. You can use theterms_set
query to return documents that match a subset of these permissions.
Example request
Index setup
In most cases, you’ll need to include a numeric field mapping in
your index to use the terms_set
query. This numeric field contains the
number of matching terms required to return a document.
To see how you can set up an index for the terms_set
query, try the
following example.
-
Create an index,
job-candidates
, with the following field mappings:-
name
, akeyword
field. This field contains the name of the job candidate. -
programming_languages
, akeyword
field. This field contains programming languages known by the job candidate. -
required_matches
, a numericlong
field. This field contains the number of matching terms required to return a document.
PUT /job-candidates { "mappings": { "properties": { "name": { "type": "keyword" }, "programming_languages": { "type": "keyword" }, "required_matches": { "type": "long" } } } }
-
-
Index a document with an ID of
1
and the following values:-
Jane Smith
in thename
field. -
["c++", "java"]
in theprogramming_languages
field. -
2
in therequired_matches
field.
Include the
?refresh
parameter so the document is immediately available for search.PUT /job-candidates/_doc/1?refresh { "name": "Jane Smith", "programming_languages": [ "c++", "java" ], "required_matches": 2 }
-
-
Index another document with an ID of
2
and the following values:-
Jason Response
in thename
field. -
["java", "php"]
in theprogramming_languages
field. -
2
in therequired_matches
field.
PUT /job-candidates/_doc/2?refresh { "name": "Jason Response", "programming_languages": [ "java", "php" ], "required_matches": 2 }
-
You can now use the required_matches
field value as the number of
matching terms required to return a document in the terms_set
query.
Example query
The following search returns documents where the programming_languages
field
contains at least two of the following terms:
-
c++
-
java
-
php
The minimum_should_match_field
is required_matches
. This means the
number of matching terms required is 2
, the value of the required_matches
field.
GET /job-candidates/_search
{
"query": {
"terms_set": {
"programming_languages": {
"terms": [ "c++", "java", "php" ],
"minimum_should_match_field": "required_matches"
}
}
}
}
Top-level parameters for terms_set
<field>
-
(Required, object) Field you wish to search.
Parameters for <field>
terms
-
(Required, array of strings) Array of terms you wish to find in the provided
<field>
. To return a document, a required number of terms must exactly match the field values, including whitespace and capitalization.The required number of matching terms is defined in the
minimum_should_match_field
orminimum_should_match_script
parameter. minimum_should_match_field
-
(Optional, string) Numeric field containing the number of matching terms required to return a document.
minimum_should_match_script
-
(Optional, string) Custom script containing the number of matching terms required to return a document.
For parameters and valid values, see Scripting.
For an example query using the
minimum_should_match_script
parameter, see How to use theminimum_should_match_script
parameter.
Notes
How to use the minimum_should_match_script
parameter
You can use minimum_should_match_script
to define the required number of
matching terms using a script. This is useful if you need to set the number of
required terms dynamically.
Example query using minimum_should_match_script
The following search returns documents where the programming_languages
field
contains at least two of the following terms:
-
c++
-
java
-
php
The source
parameter of this query indicates:
-
The required number of terms to match cannot exceed
params.num_terms
, the number of terms provided in theterms
field. -
The required number of terms to match is
2
, the value of therequired_matches
field.
GET /job-candidates/_search
{
"query": {
"terms_set": {
"programming_languages": {
"terms": [ "c++", "java", "php" ],
"minimum_should_match_script": {
"source": "Math.min(params.num_terms, doc['required_matches'].value)"
},
"boost": 1.0
}
}
}
}
Type Query
Filters documents matching the provided document/mapping type. Types are deprecated.
GET /_search
{
"query": {
"type": {
"value": "_doc"
}
}
}
Wildcard query
Returns documents that contain terms matching a wildcard pattern.
A wildcard operator is a placeholder that matches one or more characters. For
example, the *
wildcard operator matches zero or more characters. You can
combine wildcard operators with other characters to create a wildcard pattern.
Example request
The following search returns documents where the user.id
field contains a term
that begins with ki
and ends with y
. These matching terms can include kiy
,
kity
, or bilbo
.
GET /_search
{
"query": {
"wildcard": {
"user.id": {
"value": "ki*y",
"boost": 1.0,
"rewrite": "constant_score"
}
}
}
}
Top-level parameters for wildcard
<field>
-
(Required, object) Field you wish to search.
Parameters for <field>
value
-
(Required, string) Wildcard pattern for terms you wish to find in the provided
<field>
.This parameter supports two wildcard operators:
-
?
, which matches any single character -
*
, which can match zero or more characters, including an empty one
WarningAvoid beginning patterns with *
or?
. This can increase the iterations needed to find matching terms and slow search performance. -
boost
-
(Optional, float) Floating point number used to decrease or increase the relevance scores of a query. Defaults to
1.0
.You can use the
boost
parameter to adjust relevance scores for searches containing two or more queries.Boost values are relative to the default value of
1.0
. A boost value between0
and1.0
decreases the relevance score. A value greater than1.0
increases the relevance score. rewrite
-
(Optional, string) Method used to rewrite the query. For valid values and more information, see the
rewrite
parameter. case_insensitive
-
(Optional, Boolean) allows case insensitive matching of the pattern with the indexed field values when set to true. Default is false which means the case sensitivity of matching depends on the underlying field’s mapping.
Notes
Allow expensive queries
Wildcard queries will not be executed if search.allow_expensive_queries
is set to false.


Secret Management
Edit (pull request)This section describe in a transverse manner how to configure a secret provider (such as HashiCorp Vault), how to declare / use a secret for a deployment.
Pre-requisite
Alien4Cloud offers the ability to integrate any secret provider thanks to its plugin system. For the moment only one plugin is provided for HashiCorp Vault but that can change in the future.
HashiCorp Vault
Alien4Cloud is not responsible for storing your secrets, the task is delegated an external HashiCorp Vault. It should be properly installed, unsealed and configured:
Configure
Administrator should configure a Secret Vault on the orchestrator location.
To associate a secret provider (such as HashiCorp Vault) to the location, please refer to this page.
Usage
In Tosca Yaml
get_secret function details can be found on this page.
In Topology Editor
get_secret function can be declared on node’s properties, please take a look here for more details.
In deployment’s input
get_secret function can be declared on deployment’s inputs, please take a look here for more details.
In location’s resources properties
get_secret function can be declared on properties of location resources
In service’s properties and attributes
get_secret function can be declared on service’s properties and attributes
Runtime
When an application deployment is associated with a location with Secret Vault enabled (configured), each deployer’s action (workflow execution, for example deploy, undeploy …) will bring up a modal so that the deployer can enter the Vault credentials.
The credentials will be checked and used by Alien4Cloud and the underlying orchestrator to resolve secrets declared in your deployment (inputs, properties etc …).
If your action does not need to access to a secret vault, you can click on Skip but then the action will fail at orchestrator runtime level if a secret is needed.
List of actions that brings up secret credentials modal:
- Deploy
- Undeploy
- Update
- Scale
- Custom command execution
- Custom workflow execution
- Post deployment operation
- Patch
Under the hood for HashiCorp Vault and Cloudify orchestrator, to resolve secret for an action:
- Alien4Cloud log in with user’s provided credentials, generate a token if necessary (for LDAP authentication method for example).
- Alien4Cloud sends the deployment with the Vault’s configuration and the token to Cloudify orchestrator.
- The token is saved inside Cloudify’s internal Vault for the duration of the action.
- Secrets are retrieved and injected just before script’s execution by using the token in Cloudify’s internal Vault.


Uses of Package
org.bukkit.potion
Package
Description
The root package of the Bukkit API, contains generalized API classes.
Classes used to manipulate the voxels in a
world
,
including special states.Interfaces for non-voxel objects that can exist in a
world
, including all players, monsters, projectiles, etc.The interfaces used when manipulating extra data can can be stored inside
item stacks
.Classes to represent various
potion
properties and manipulation.-
-
-
ClassDescriptionRepresents a brewer that can create
PotionEffect
s.Represents a type of potion and its effect on an entity. -
ClassDescriptionRepresents a potion effect, that can be added to a
LivingEntity
.Represents a type of potion and its effect on an entity. -
ClassDescriptionRepresents a potion effect, that can be added to a
LivingEntity
.Represents a type of potion and its effect on an entity. -
ClassDescriptionRepresents a potion effect, that can be added to a
LivingEntity
.Represents a type of potion and its effect on an entity. -
ClassDescriptionRepresents a potion effect, that can be added to a
LivingEntity
.Represents a type of potion and its effect on an entity. -
ClassDescriptionDeprecated.Represents a brewer that can create
PotionEffect
s.Represents a potion effect, that can be added to aLivingEntity
.Represents a type of potion and its effect on an entity.Category ofPotionEffectType
sThis enum reflects and matches each potion state that can be obtained from the Creative mode inventory


Last updated: 2020-06-25
Checks: 7 0
Knit directory: smash-paper/analysis/
This reproducible R Markdown analysis was created with workflowr (version 1.6.2). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.
Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.
Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.
The command set.seed(1)
was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.
Great job! Recording the operating system, R version, and package versions is critical for reproducibility.
Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.
Great job! Using relative paths to the files within your workflowr project makes it easier to run your code on other machines.
Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.
The results in this page were generated with repository version 6fd9dd8. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.
Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish
or wflow_git_commit
). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:
Ignored files:
Ignored: dsc/code/Wavelab850/MEXSource/CPAnalysis.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/DownDyadHi.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/DownDyadLo.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/FAIPT.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/FCPSynthesis.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/FMIPT.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/FWPSynthesis.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/FWT2_PO.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/FWT_PBS.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/FWT_PO.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/FWT_TI.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/IAIPT.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/IMIPT.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/IWT2_PO.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/IWT_PBS.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/IWT_PO.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/IWT_TI.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/LMIRefineSeq.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/MedRefineSeq.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/UpDyadHi.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/UpDyadLo.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/WPAnalysis.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/dct_ii.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/dct_iii.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/dct_iv.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/dst_ii.mexmac
Ignored: dsc/code/Wavelab850/MEXSource/dst_iii.mexmac
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
These are the previous versions of the repository in which changes were made to the R Markdown (analysis/poisson.Rmd
) and HTML (docs/poisson.html
) files. If you’ve configured a remote Git repository (see ?wflow_git_remote
), click on the hyperlinks in the table below to view the files as they were in that past version.
| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | 6fd9dd8 | Peter Carbonetto | 2020-06-25 | wflow_publish(“poisson.Rmd”) |
| html | a40b191 | Peter Carbonetto | 2020-06-25 | Added fitted curves to Spikes plot in poisson demo. |
| Rmd | 24bf5c4 | Peter Carbonetto | 2020-06-25 | Added example run of smash and HF methods to poisson demo. |
| html | 124e2e5 | Peter Carbonetto | 2020-06-23 | Slight edit to plotting code in “poisson” workflowr analysis. |
| Rmd | bfb662b | Peter Carbonetto | 2020-06-23 | A few small revisions to the workflowr analyses. |
| html | fe1c0ea | Peter Carbonetto | 2019-12-20 | Build site. |
| Rmd | fe98ca6 | Peter Carbonetto | 2019-12-20 | wflow_publish(“poisson.Rmd”) |
| html | b369c4d | Peter Carbonetto | 2019-12-16 | Re-built poisson analysis after fixing create.signal.plot(). |
| Rmd | 0f4dc2e | Peter Carbonetto | 2019-12-16 | wflow_publish(“poisson.Rmd”) |
| html | 8398464 | Peter Carbonetto | 2019-12-16 | Added set.seed to poisson.Rmd. |
| Rmd | a10397e | Peter Carbonetto | 2019-12-16 | wflow_publish(“poisson.Rmd”) |
| html | ddc42e3 | Peter Carbonetto | 2019-12-16 | Added data points to plots to illustrate Poisson simulations. |
| Rmd | 323d535 | Peter Carbonetto | 2019-12-16 | wflow_publish(“poisson.Rmd”) |
| Rmd | 00cf92a | Peter Carbonetto | 2019-12-16 | Implemented function create.signal.plot in poisson.functions.R. |
| html | 00cf92a | Peter Carbonetto | 2019-12-16 | Implemented function create.signal.plot in poisson.functions.R. |
| Rmd | aca0299 | Peter Carbonetto | 2019-11-14 | Small edit to code in poisson.Rmd. |
| html | b013a9f | Peter Carbonetto | 2019-11-14 | Adjusted bar plots in Poisson simulations analysis. |
| html | 3a62540 | Peter Carbonetto | 2019-11-14 | Added bar charts summarizing results of Poisson simulations. |
| Rmd | c143a8f | Peter Carbonetto | 2019-11-14 | wflow_publish(“poisson.Rmd”) |
| html | d7735d5 | Peter Carbonetto | 2019-11-13 | Made some improvements to the code for creating the violin plots in |
| Rmd | f6a2109 | Peter Carbonetto | 2019-11-13 | wflow_publish(“poisson.Rmd”) |
| Rmd | dded357 | Peter Carbonetto | 2019-11-13 | Some small adjustments to the plotting code in poisson.Rmd. |
| html | 248e31e | Peter Carbonetto | 2019-11-13 | Re-built poisson analysis after simplifying creation of a violin plot. |
| Rmd | 06f113f | Peter Carbonetto | 2019-11-13 | wflow_publish(“poisson.Rmd”) |
| html | 8925b13 | Peter Carbonetto | 2019-11-12 | Re-built poisson analysis after implementing Bursts and Heavisine functions. |
| Rmd | 4576145 | Peter Carbonetto | 2019-11-12 | wflow_publish(“poisson.Rmd”) |
| html | c890a40 | Peter Carbonetto | 2019-11-12 | Re-ran poisson and gaussian_signals analyses with new code in signals.R. |
| Rmd | 1f76230 | Peter Carbonetto | 2019-11-12 | Restructured some of the code in signals.R. |
| html | 1f76230 | Peter Carbonetto | 2019-11-12 | Restructured some of the code in signals.R. |
| Rmd | 35a397a | Peter Carbonetto | 2019-11-12 | Simplifying some of the code in poisson.Rmd. |
| html | 187ec0c | Peter Carbonetto | 2019-11-12 | Fixed formatting of table in poisson analysis. |
| Rmd | 05e491f | Peter Carbonetto | 2019-11-12 | wflow_publish(“poisson.Rmd”) |
| html | a334fd2 | Peter Carbonetto | 2019-11-12 | More adjustments to plots in poisson analysis. |
| Rmd | 224a580 | Peter Carbonetto | 2019-11-12 | wflow_publish(“poisson.Rmd”) |
| html | 34f42ac | Peter Carbonetto | 2019-11-12 | Adjusted violin plots in poisson analysis. |
| Rmd | 8333706 | Peter Carbonetto | 2019-11-12 | wflow_publish(“poisson.Rmd”) |
| html | eda1295 | Peter Carbonetto | 2019-11-12 | Re-built poisson analysis using workflowr 1.5.0. |
| Rmd | a0ea389 | Peter Carbonetto | 2019-11-12 | wflow_publish(“poisson.Rmd”) |
| html | f0221c5 | Zhengrong Xing | 2019-10-27 | address some reviewer comments |
| html | bf8b368 | Peter Carbonetto | 2018-12-21 | Fixed plots for Bursts simulations. |
| Rmd | b9f5cd3 | Peter Carbonetto | 2018-12-21 | wflow_publish(c(“index.Rmd”, “poisson.Rmd”)) |
| html | 3441667 | Peter Carbonetto | 2018-12-21 | Revised Bumps results in poisson.Rmd. |
| Rmd | 7db6b71 | Peter Carbonetto | 2018-12-21 | wflow_publish(“poisson.Rmd”) |
| html | ee06399 | Peter Carbonetto | 2018-12-21 | Added plots & tables for Clipped Blocks and Bumps simulations. |
| Rmd | e8bc009 | Peter Carbonetto | 2018-12-21 | wflow_publish(“poisson.Rmd”) |
| html | 5adee34 | Peter Carbonetto | 2018-12-21 | Addd plots and table for Bursts simulations. |
| Rmd | 3776af8 | Peter Carbonetto | 2018-12-21 | wflow_publish(“poisson.Rmd”) |
| html | c333197 | Peter Carbonetto | 2018-12-21 | A few small revsions to the code at the beginning of poisson.Rmd. |
| Rmd | b42715c | Peter Carbonetto | 2018-12-21 | wflow_publish(“poisson.Rmd”) |
| html | 8e3900b | Peter Carbonetto | 2018-12-21 | Updated text at the beginning of poisson.Rmd. |
| Rmd | d351039 | Peter Carbonetto | 2018-12-21 | wflow_publish(“poisson.Rmd”) |
| html | bd84eae | Peter Carbonetto | 2018-12-20 | Build site. |
| Rmd | 51620b3 | Peter Carbonetto | 2018-12-20 | wflow_publish(“poisson.Rmd”) |
| html | bda4fbc | Peter Carbonetto | 2018-12-20 | Wrote function create.violin.plots in poisson.Rmd. |
| Rmd | ed77c12 | Peter Carbonetto | 2018-12-20 | Fixed some merging issues. |
| html | ed961b1 | Peter Carbonetto | 2018-12-20 | Added violin plots for the Spikes and Angles Poisson simulation results. |
| Rmd | 68ce493 | Peter Carbonetto | 2018-12-20 | wflow_publish(“poisson.Rmd”) |
| html | 2acee22 | Peter Carbonetto | 2018-12-20 | Added plots for all test functions. |
| html | 78afaca | Peter Carbonetto | 2018-12-20 | Added plots for all test functions. |
| Rmd | 987a861 | Peter Carbonetto | 2018-12-20 | wflow_publish(“poisson.Rmd”) |
| html | 7908551 | Peter Carbonetto | 2018-12-20 | Built very first draft of the “poisson” workflowr page. |
| Rmd | b3f5b57 | Peter Carbonetto | 2018-12-20 | wflow_publish(“poisson.Rmd”) |
| Rmd | d36bfca | Peter Carbonetto | 2018-12-20 | Misc. revisions to READMEs and documentation. |
| Rmd | 7aa0b11 | Peter Carbonetto | 2018-12-20 | Working on poisson analysis. |
| Rmd | 3c562ea | Peter Carbonetto | 2018-12-19 | Moved poisson_tables.Rmd to poisson.Rmd. |
| Rmd | 190c855 | Peter Carbonetto | 2018-12-19 | Working on R Markdown for Poisson results. |
| Rmd | 25ff9c3 | Peter Carbonetto | 2018-12-19 | Re-organized some of the files used in the Poisson numerical comparisons. |
Here we create plots and tables to compare various methods, including SMASH, for reconstructing a spatially structured signal from Poisson-distributed data. Similar to the Gaussian simulations, we generated data sets using a variety of test functions and intensity ranges. Specifically, we considered 6 test functions, rescaling the test function so that the smallest intensity was \(x\) and the largest intensity was \(y\), with \((x,y)\) set to either \((1/100, 3)\), \((1/8, 8)\) or \((1/128, 128)\).
For each combination of test function and intensity range, we simulated 100 data sets. In the plots and tables below, we summarize the error (MISE) in the estimates computed in the 100 data sets from each simulation setting. A final summary of all the simulations is shown at the end.
The plots shown below for the “Bursts” simulations, as well as the bar plots summarizing all the Poisson simulations, were included in the manuscript.
We will view the results from these methods:
methods <- c("ash","BMSM","haarfisz_R")
These variables specify the row and column names for the tables:
These are settings used in plotting the test functions:
n <- 1024
t <- 1:n/n
Load the plyr, knitr, kableExtra, ggplot2 and cowplot packages.
library(smashr)
library(haarfisz)
library(plyr)
library(knitr)
library(kableExtra)
library(ggplot2)
library(cowplot)
theme_set(theme_cowplot())
Some of the test functions are defined in signals.R
, so we load them here. Some additional functions are defined in file poisson.functions.R
.
source("../code/signals.R")
source("../code/poisson.functions.R")
Initialize the sequence of pseudorandom numbers.
set.seed(1)
Load the results of the simulation experiments.
load("../output/pois.RData")
This plot shows the function used to simulate the “Spikes” data sets at the \((1/100, 3)\) intensity range. We also show an example data set simulated from the Spikes intensity function (black circles), and the fitted curves obtained by applying SMASH (orange) and the Haar-Fisz method (light blue) to these data:
mu.s <- 0.01 + spike.f(t)
x <- rpois(n,mu.s)
out.hf <- denoise.poisson(x,meth.1 = hf.la10.ti4,cs.1 = 50,hybrid = FALSE)
out.smash <- smash.poiss(x,post.var = TRUE)
p1 <- create.signal.plot(t,x,mu.s) +
geom_line(dat = data.frame(x = t,y = out.smash$est),col = "darkorange") +
geom_line(dat = data.frame(x = t,y = out.hf),col = "dodgerblue")
print(p1)
| Version | Author | Date |
|---|---|---|
| a40b191 | Peter Carbonetto | 2020-06-25 |
| 124e2e5 | Peter Carbonetto | 2020-06-23 |
| 00cf92a | Peter Carbonetto | 2019-12-16 |
| a334fd2 | Peter Carbonetto | 2019-11-12 |
| eda1295 | Peter Carbonetto | 2019-11-12 |
| f0221c5 | Zhengrong Xing | 2019-10-27 |
| bda4fbc | Peter Carbonetto | 2018-12-20 |
| ed77c12 | Peter Carbonetto | 2018-12-20 |
| ed961b1 | Peter Carbonetto | 2018-12-20 |
| 2acee22 | Peter Carbonetto | 2018-12-20 |
| 78afaca | Peter Carbonetto | 2018-12-20 |
This table summarizes the results from the Spikes simulations:
mise.s.table <- cbind(mise.s.1[methods],
mise.s.8[methods],
mise.s.128[methods])
create.results.table(mise.s.table)
| (1/100, 3) | (1/8, 8) | (1/128, 128) | |
|---|---|---|---|
| SMASH | 690.0116 | 329.2584 | 48.86856 |
| BMSM | 1007.3414 | 397.7901 | 41.87725 |
| Haar-Fisz | 722.1856 | 287.4406 | 18.05736 |
Each column shows the results at a different range of intensities. The individual table entries give the average error (MISE) in the estimates, in which the average is taken over the 100 data sets simulated at the given range of intensities.
The combined violin-boxplots provide a more detailed summary of the same results:
mise.hf.ti.r.s.1 <- colMeans(rbind(mise.hf.ti.r.4.s.1,
mise.hf.ti.r.5.s.1,
mise.hf.ti.r.6.s.1,
mise.hf.ti.r.7.s.1))
mise.hf.ti.r.s.8 <- colMeans(rbind(mise.hf.ti.r.4.s.8,
mise.hf.ti.r.5.s.8,
mise.hf.ti.r.6.s.8,
mise.hf.ti.r.7.s.8))
mise.hf.ti.r.s.128 <- colMeans(rbind(mise.hf.ti.r.4.s.128,
mise.hf.ti.r.5.s.128,
mise.hf.ti.r.6.s.128,
mise.hf.ti.r.7.s.128))
pdat.s1 <- get.violin.plot.data(list("Haar-Fisz" = mise.hf.ti.r.s.1,
"BMSM" = mise.BMSM.s.1,
"SMASH" = mise.ash.s.1))
pdat.s8 <- get.violin.plot.data(list("Haar-Fisz" = mise.hf.ti.r.s.8,
"BMSM" = mise.BMSM.s.8,
"SMASH" = mise.ash.s.8))
pdat.s128 <- get.violin.plot.data(list("Haar-Fisz" = mise.hf.ti.r.s.128,
"BMSM" = mise.BMSM.s.128,
"SMASH" = mise.ash.s.128))
create.violin.plots(pdat.s1,pdat.s8,pdat.s128)
| Version | Author | Date |
|---|---|---|
| 124e2e5 | Peter Carbonetto | 2020-06-23 |
| 187ec0c | Peter Carbonetto | 2019-11-12 |
| a334fd2 | Peter Carbonetto | 2019-11-12 |
| 34f42ac | Peter Carbonetto | 2019-11-12 |
| eda1295 | Peter Carbonetto | 2019-11-12 |
| f0221c5 | Zhengrong Xing | 2019-10-27 |
| bda4fbc | Peter Carbonetto | 2018-12-20 |
| ed961b1 | Peter Carbonetto | 2018-12-20 |
This is the function used to simulate the “Angles” data sets at different ranges of intensities. We also show an example data set simulated from the Angles intensity function (black circles), and the fitted curves obtained by applying SMASH (orange) and the Haar-Fisz method (light blue) to these data:
mu.ang <- 0.01 + angles.f(t)
x <- rpois(n,mu.ang)
out.hf <- denoise.poisson(x,meth.1 = hf.la10.ti4,cs.1 = 50,hybrid = FALSE)
out.smash <- smash.poiss(x,post.var = TRUE)
p2 <- create.signal.plot(t,x,mu.ang) +
geom_line(dat = data.frame(x = t,y = out.smash$est),col = "darkorange") +
geom_line(dat = data.frame(x = t,y = out.hf),col = "dodgerblue")
print(p2)
| Version | Author | Date |
|---|---|---|
| a40b191 | Peter Carbonetto | 2020-06-25 |
| 124e2e5 | Peter Carbonetto | 2020-06-23 |
| 00cf92a | Peter Carbonetto | 2019-12-16 |
| a334fd2 | Peter Carbonetto | 2019-11-12 |
| eda1295 | Peter Carbonetto | 2019-11-12 |
| f0221c5 | Zhengrong Xing | 2019-10-27 |
| bda4fbc | Peter Carbonetto | 2018-12-20 |
| ed77c12 | Peter Carbonetto | 2018-12-20 |
| ed961b1 | Peter Carbonetto | 2018-12-20 |
| 2acee22 | Peter Carbonetto | 2018-12-20 |
| 78afaca | Peter Carbonetto | 2018-12-20 |
This table summarizes the results from the Angles simulations:
mise.ang.table <- cbind(mise.ang.1[methods],
mise.ang.8[methods],
mise.ang.128[methods])
create.results.table(mise.ang.table)
| (1/100, 3) | (1/8, 8) | (1/128, 128) | |
|---|---|---|---|
| SMASH | 145.2623 | 68.47102 | 10.249294 |
| BMSM | 147.3973 | 73.86633 | 10.491953 |
| Haar-Fisz | 314.4088 | 122.79203 | 9.082691 |
Each column shows the results at a different range of intensities. The individual table entries give the average error (MISE) in the estimates, in which the average is taken over the 100 data sets simulated at the given range of intensities.
The combined violin-boxplots provide a visualization of the same results:
mise.hf.ti.r.ang.1 <- colMeans(rbind(mise.hf.ti.r.4.ang.1,
mise.hf.ti.r.5.ang.1,
mise.hf.ti.r.6.ang.1,
mise.hf.ti.r.7.ang.1))
mise.hf.ti.r.ang.8 <- colMeans(rbind(mise.hf.ti.r.4.ang.8,
mise.hf.ti.r.5.ang.8,
mise.hf.ti.r.6.ang.8,
mise.hf.ti.r.7.ang.8))
mise.hf.ti.r.ang.128 <- colMeans(rbind(mise.hf.ti.r.4.ang.128,
mise.hf.ti.r.5.ang.128,
mise.hf.ti.r.6.ang.128,
mise.hf.ti.r.7.ang.128))
pdat.ang1 <- get.violin.plot.data(list("Haar-Fisz" = mise.hf.ti.r.ang.1,
"BMSM" = mise.BMSM.ang.1,
"SMASH" = mise.ash.ang.1))
pdat.ang8 <- get.violin.plot.data(list("Haar-Fisz" = mise.hf.ti.r.ang.8,
"BMSM" = mise.BMSM.ang.8,
"SMASH" = mise.ash.ang.8))
pdat.ang128 <- get.violin.plot.data(list("Haar-Fisz" = mise.hf.ti.r.ang.128,
"BMSM" = mise.BMSM.ang.128,
"SMASH" = mise.ash.ang.128))
create.violin.plots(pdat.ang1,pdat.ang8,pdat.ang128)
| Version | Author | Date |
|---|---|---|
| 124e2e5 | Peter Carbonetto | 2020-06-23 |
| 187ec0c | Peter Carbonetto | 2019-11-12 |
| a334fd2 | Peter Carbonetto | 2019-11-12 |
| 34f42ac | Peter Carbonetto | 2019-11-12 |
| eda1295 | Peter Carbonetto | 2019-11-12 |
| f0221c5 | Zhengrong Xing | 2019-10-27 |
| bda4fbc | Peter Carbonetto | 2018-12-20 |
| ed961b1 | Peter Carbonetto | 2018-12-20 |
This is the function used to simulate the “Heavisine” data sets at different ranges of intensities. We also show an example data set simulated from the Heavisine intensity function (black circles), and the fitted curves obtained by applying SMASH (orange) and the Haar-Fisz method (light blue) to these data:
mu.hs <- 0.01 + heavi.f(t)
x <- rpois(n,mu.hs)
out.hf <- denoise.poisson(x,meth.1 = hf.la10.ti4,cs.1 = 50,hybrid = FALSE)
out.smash <- smash.poiss(x,post.var = TRUE)
p3 <- create.signal.plot(t,x,mu.hs) +
geom_line(dat = data.frame(x = t,y = out.smash$est),col = "darkorange") +
geom_line(dat = data.frame(x = t,y = out.hf),col = "dodgerblue")
print(p3)
| Version | Author | Date |
|---|---|---|
| a40b191 | Peter Carbonetto | 2020-06-25 |
| 124e2e5 | Peter Carbonetto | 2020-06-23 |
| 00cf92a | Peter Carbonetto | 2019-12-16 |
| a334fd2 | Peter Carbonetto | 2019-11-12 |
| eda1295 | Peter Carbonetto | 2019-11-12 |
| f0221c5 | Zhengrong Xing | 2019-10-27 |
| bda4fbc | Peter Carbonetto | 2018-12-20 |
| ed77c12 | Peter Carbonetto | 2018-12-20 |
| ed961b1 | Peter Carbonetto | 2018-12-20 |
| 2acee22 | Peter Carbonetto | 2018-12-20 |
| 78afaca | Peter Carbonetto | 2018-12-20 |
This table summarizes the results from the Heavisine simulations:
mise.hs.table <- cbind(mise.hs.1[methods],
mise.hs.8[methods],
mise.hs.128[methods])
create.results.table(mise.hs.table)
| (1/100, 3) | (1/8, 8) | (1/128, 128) | |
|---|---|---|---|
| SMASH | 81.41384 | 43.21293 | 7.213658 |
| BMSM | 85.28578 | 44.22229 | 7.353458 |
| Haar-Fisz | 274.25562 | 105.47241 | 9.225844 |
Each column shows results at a different range of intensities. The individual table entries give the average error (MISE) in the estimates, in which the average is taken over the 100 data sets simulated at the given range of intensities.
The combined violin-boxplots provide a visualization of the same results:
mise.hf.ti.r.hs.1 <- colMeans(rbind(mise.hf.ti.r.4.hs.1,
mise.hf.ti.r.5.hs.1,
mise.hf.ti.r.6.hs.1,
mise.hf.ti.r.7.hs.1))
mise.hf.ti.r.hs.8 <- colMeans(rbind(mise.hf.ti.r.4.hs.8,
mise.hf.ti.r.5.hs.8,
mise.hf.ti.r.6.hs.8,
mise.hf.ti.r.7.hs.8))
mise.hf.ti.r.hs.128 <- colMeans(rbind(mise.hf.ti.r.4.hs.128,
mise.hf.ti.r.5.hs.128,
mise.hf.ti.r.6.hs.128,
mise.hf.ti.r.7.hs.128))
pdat.hs1 <- get.violin.plot.data(list("Haar-Fisz" = mise.hf.ti.r.hs.1,
"BMSM" = mise.BMSM.hs.1,
"SMASH" = mise.ash.hs.1))
pdat.hs8 <- get.violin.plot.data(list("Haar-Fisz" = mise.hf.ti.r.hs.8,
"BMSM" = mise.BMSM.hs.8,
"SMASH" = mise.ash.hs.8))
pdat.hs128 <- get.violin.plot.data(list("Haar-Fisz" = mise.hf.ti.r.hs.128,
"BMSM" = mise.BMSM.hs.128,
"SMASH" = mise.ash.hs.128))
create.violin.plots(pdat.hs1,pdat.hs8,pdat.hs128)
This is the function used to simulate the “Bursts” data sets at different ranges of intensities. We also show an example data set simulated from the Bursts intensity function (black circles), and the fitted curves obtained by applying SMASH (orange) and the Haar-Fisz method (light blue) to these data:
mu.bur <- 0.01 + bursts.f(t)
x <- rpois(n,mu.bur)
out.hf <- denoise.poisson(x,meth.1 = hf.la10.ti4,cs.1 = 50,hybrid = FALSE)
out.smash <- smash.poiss(x,post.var = TRUE)
p4 <- create.signal.plot(t,x,mu.bur) +
geom_line(dat = data.frame(x = t,y = out.smash$est),col = "darkorange") +
geom_line(dat = data.frame(x = t,y = out.hf),col = "dodgerblue")
print(p4)
| Version | Author | Date |
|---|---|---|
| a40b191 | Peter Carbonetto | 2020-06-25 |
| 124e2e5 | Peter Carbonetto | 2020-06-23 |
| ddc42e3 | Peter Carbonetto | 2019-12-16 |
| a334fd2 | Peter Carbonetto | 2019-11-12 |
| eda1295 | Peter Carbonetto | 2019-11-12 |
| f0221c5 | Zhengrong Xing | 2019-10-27 |
| bda4fbc | Peter Carbonetto | 2018-12-20 |
| ed77c12 | Peter Carbonetto | 2018-12-20 |
| ed961b1 | Peter Carbonetto | 2018-12-20 |
| 2acee22 | Peter Carbonetto | 2018-12-20 |
| 78afaca | Peter Carbonetto | 2018-12-20 |
This table summarizes the results from the Bursts simulations:
mise.bur.table <- cbind(mise.bur.1[methods],
mise.bur.8[methods],
mise.bur.128[methods])
create.results.table(mise.bur.table)
| (1/100, 3) | (1/8, 8) | (1/128, 128) | |
|---|---|---|---|
| SMASH | 487.3353 | 234.3490 | 33.11112 |
| BMSM | 706.0353 | 301.8645 | 34.42320 |
| Haar-Fisz | 618.3874 | 299.3932 | 25.19659 |
Each column shows results at a different range of intensities. The individual table entries give the average error (MISE) in the estimates, in which the average is taken over the 100 data sets simulated at the given range of intensities.
The combined violin-boxplots provide a visualization of the same results:
mise.hf.ti.r.bur.1 <- colMeans(rbind(mise.hf.ti.r.4.bur.1,
mise.hf.ti.r.5.bur.1,
mise.hf.ti.r.6.bur.1,
mise.hf.ti.r.7.bur.1))
mise.hf.ti.r.bur.8 <- colMeans(rbind(mise.hf.ti.r.4.bur.8,
mise.hf.ti.r.5.bur.8,
mise.hf.ti.r.6.bur.8,
mise.hf.ti.r.7.bur.8))
mise.hf.ti.r.bur.128 <- colMeans(rbind(mise.hf.ti.r.4.bur.128,
mise.hf.ti.r.5.bur.128,
mise.hf.ti.r.6.bur.128,
mise.hf.ti.r.7.bur.128))
pdat.bur1 <- get.violin.plot.data(list("Haar-Fisz" = mise.hf.ti.r.bur.1,
"BMSM" = mise.BMSM.bur.1,
"SMASH" = mise.ash.bur.1))
pdat.bur8 <- get.violin.plot.data(list("Haar-Fisz" = mise.hf.ti.r.bur.8,
"BMSM" = mise.BMSM.bur.8,
"SMASH" = mise.ash.bur.8))
pdat.bur128 <- get.violin.plot.data(list("Haar-Fisz" = mise.hf.ti.r.bur.128,
"BMSM" = mise.BMSM.bur.128,
"SMASH" = mise.ash.bur.128))
create.violin.plots(pdat.bur1,pdat.bur8,pdat.bur128)
This is the function used to simulate the “Clipped Blocks” data sets at different ranges of intensities. We also show an example data set simulated from the Clipped Blocks intensity function (black circles), and the fitted curves obtained by applying SMASH (orange) and the Haar-Fisz method (light blue) to these data:
mu.cb <- 0.01 + cblocks.f(t)
x <- rpois(n,mu.cb)
out.hf <- denoise.poisson(x,meth.1 = hf.la10.ti4,cs.1 = 50,hybrid = FALSE)
out.smash <- smash.poiss(x,post.var = TRUE)
p5 <- create.signal.plot(t,x,mu.cb) +
geom_line(dat = data.frame(x = t,y = out.smash$est),col = "darkorange") +
geom_line(dat = data.frame(x = t,y = out.hf),col = "dodgerblue")
print(p5)
| Version | Author | Date |
|---|---|---|
| a40b191 | Peter Carbonetto | 2020-06-25 |
| 124e2e5 | Peter Carbonetto | 2020-06-23 |
| fe1c0ea | Peter Carbonetto | 2019-12-20 |
| ddc42e3 | Peter Carbonetto | 2019-12-16 |
| a334fd2 | Peter Carbonetto | 2019-11-12 |
| eda1295 | Peter Carbonetto | 2019-11-12 |
| f0221c5 | Zhengrong Xing | 2019-10-27 |
| bda4fbc | Peter Carbonetto | 2018-12-20 |
| ed77c12 | Peter Carbonetto | 2018-12-20 |
| ed961b1 | Peter Carbonetto | 2018-12-20 |
| 2acee22 | Peter Carbonetto | 2018-12-20 |
| 78afaca | Peter Carbonetto | 2018-12-20 |
This table summarizes the results from the Clipped Blocks simulations:
mise.cb.table <- cbind(mise.cb.1[methods],
mise.cb.8[methods],
mise.cb.128[methods])
create.results.table(mise.cb.table)
| (1/100, 3) | (1/8, 8) | (1/128, 128) | |
|---|---|---|---|
| SMASH | 307.8030 | 137.2787 | 6.822219 |
| BMSM | 355.1542 | 143.0926 | 6.911608 |
| Haar-Fisz | 632.2052 | 338.5486 | 29.719806 |
Each column shows results at a different range of intensities. The individual table entries give the average error (MISE) in the estimates, in which the average is taken over the 100 data sets simulated at the given range of intensities.
The combined violin-boxplots provide a visualization of the same results:
mise.hf.ti.r.cb.1 <- colMeans(rbind(mise.hf.ti.r.4.cb.1,
mise.hf.ti.r.5.cb.1,
mise.hf.ti.r.6.cb.1,
mise.hf.ti.r.7.cb.1))
mise.hf.ti.r.cb.8 <- colMeans(rbind(mise.hf.ti.r.4.cb.8,
mise.hf.ti.r.5.cb.8,
mise.hf.ti.r.6.cb.8,
mise.hf.ti.r.7.cb.8))
mise.hf.ti.r.cb.128 <- colMeans(rbind(mise.hf.ti.r.4.cb.128,
mise.hf.ti.r.5.cb.128,
mise.hf.ti.r.6.cb.128,
mise.hf.ti.r.7.cb.128))
pdat.cb1 <- get.violin.plot.data(list("Haar-Fisz" = mise.hf.ti.r.cb.1,
"BMSM" = mise.BMSM.cb.1,
"SMASH" = mise.ash.cb.1))
pdat.cb8 <- get.violin.plot.data(list("Haar-Fisz" = mise.hf.ti.r.cb.8,
"BMSM" = mise.BMSM.cb.8,
"SMASH" = mise.ash.cb.8))
pdat.cb128 <- get.violin.plot.data(list("Haar-Fisz" = mise.hf.ti.r.cb.128,
"BMSM" = mise.BMSM.cb.128,
"SMASH" = mise.ash.cb.128))
create.violin.plots(pdat.cb1,pdat.cb8,pdat.cb128)
This is the function used to simulate the “Bumps” data sets at different ranges of intensities. We also show an example data set simulated from the Bumps intensity function (black circles), and the fitted curves obtained by applying SMASH (orange) and the Haar-Fisz method (light blue) to these data:
mu.b <- 0.01 + bumps.f(t)
x <- rpois(n,mu.b)
out.hf <- denoise.poisson(x,meth.1 = hf.la10.ti4,cs.1 = 50,hybrid = FALSE)
out.smash <- smash.poiss(x,post.var = TRUE)
p6 <- create.signal.plot(t,x,mu.b) +
geom_line(dat = data.frame(x = t,y = out.smash$est),col = "darkorange") +
geom_line(dat = data.frame(x = t,y = out.hf),col = "dodgerblue")
print(p6)
| Version | Author | Date |
|---|---|---|
| a40b191 | Peter Carbonetto | 2020-06-25 |
| 124e2e5 | Peter Carbonetto | 2020-06-23 |
| fe1c0ea | Peter Carbonetto | 2019-12-20 |
| ddc42e3 | Peter Carbonetto | 2019-12-16 |
| a334fd2 | Peter Carbonetto | 2019-11-12 |
| eda1295 | Peter Carbonetto | 2019-11-12 |
| f0221c5 | Zhengrong Xing | 2019-10-27 |
| bda4fbc | Peter Carbonetto | 2018-12-20 |
| ed77c12 | Peter Carbonetto | 2018-12-20 |
| ed961b1 | Peter Carbonetto | 2018-12-20 |
| 2acee22 | Peter Carbonetto | 2018-12-20 |
| 78afaca | Peter Carbonetto | 2018-12-20 |
This table summarizes the results from the Bumps simulations:
mise.b.table <- cbind(mise.b.1[methods],
mise.b.8[methods],
mise.b.128[methods])
create.results.table(mise.b.table)
| (1/100, 3) | (1/8, 8) | (1/128, 128) | |
|---|---|---|---|
| SMASH | 2597.462 | 1194.624 | 141.2119 |
| BMSM | 4036.773 | 1889.937 | 171.0706 |
| Haar-Fisz | 3113.365 | 1658.742 | 184.6601 |
Each column shows results at a different range of intensities. The individual table entries give the average error (MISE) in the estimates, in which the average is taken over the 100 data sets simulated at the given range of intensities.
The combined violin-boxplots provide a visualization of the same results:
mise.hf.ti.r.b.1 <- colMeans(rbind(mise.hf.ti.r.4.b.1,
mise.hf.ti.r.5.b.1,
mise.hf.ti.r.6.b.1,
mise.hf.ti.r.7.b.1))
mise.hf.ti.r.b.8 <- colMeans(rbind(mise.hf.ti.r.4.b.8,
mise.hf.ti.r.5.b.8,
mise.hf.ti.r.6.b.8,
mise.hf.ti.r.7.b.8))
mise.hf.ti.r.b.128 <- colMeans(rbind(mise.hf.ti.r.4.b.128,
mise.hf.ti.r.5.b.128,
mise.hf.ti.r.6.b.128,
mise.hf.ti.r.7.b.128))
pdat.b1 <- get.violin.plot.data(list("Haar-Fisz" = mise.hf.ti.r.b.1,
"BMSM" = mise.BMSM.b.1,
"SMASH" = mise.ash.b.1))
pdat.b8 <- get.violin.plot.data(list("Haar-Fisz" = mise.hf.ti.r.b.8,
"BMSM" = mise.BMSM.b.8,
"SMASH" = mise.ash.b.8))
pdat.b128 <- get.violin.plot.data(list("Haar-Fisz" = mise.hf.ti.r.b.128,
"BMSM" = mise.BMSM.b.128,
"SMASH" = mise.ash.b.128))
create.violin.plots(pdat.b1,pdat.b8,pdat.b128)
| Version | Author | Date |
|---|---|---|
| 124e2e5 | Peter Carbonetto | 2020-06-23 |
| 187ec0c | Peter Carbonetto | 2019-11-12 |
| a334fd2 | Peter Carbonetto | 2019-11-12 |
| 34f42ac | Peter Carbonetto | 2019-11-12 |
| eda1295 | Peter Carbonetto | 2019-11-12 |
| f0221c5 | Zhengrong Xing | 2019-10-27 |
| bf8b368 | Peter Carbonetto | 2018-12-21 |
| ee06399 | Peter Carbonetto | 2018-12-21 |
These plots summarize the results for all 6 simulation scenarios.
pdat.s1$simulation <- "Spikes"
pdat.s8$simulation <- "Spikes"
pdat.s128$simulation <- "Spikes"
pdat.s1$intensity <- "(1/100, 3)"
pdat.s8$intensity <- "(1/8, 8)"
pdat.s128$intensity <- "(1/128, 128)"
pdat.ang1$simulation <- "Angles"
pdat.ang8$simulation <- "Angles"
pdat.ang128$simulation <- "Angles"
pdat.ang1$intensity <- "(1/100, 3)"
pdat.ang8$intensity <- "(1/8, 8)"
pdat.ang128$intensity <- "(1/128, 128)"
pdat.hs1$simulation <- "Heavisine"
pdat.hs8$simulation <- "Heavisine"
pdat.hs128$simulation <- "Heavisine"
pdat.hs1$intensity <- "(1/100, 3)"
pdat.hs8$intensity <- "(1/8, 8)"
pdat.hs128$intensity <- "(1/128, 128)"
pdat.bur1$simulation <- "Bursts"
pdat.bur8$simulation <- "Bursts"
pdat.bur128$simulation <- "Bursts"
pdat.bur1$intensity <- "(1/100, 3)"
pdat.bur8$intensity <- "(1/8, 8)"
pdat.bur128$intensity <- "(1/128, 128)"
pdat.cb1$simulation <- "Clipped"
pdat.cb8$simulation <- "Clipped"
pdat.cb128$simulation <- "Clipped"
pdat.cb1$intensity <- "(1/100, 3)"
pdat.cb8$intensity <- "(1/8, 8)"
pdat.cb128$intensity <- "(1/128, 128)"
pdat.b1$simulation <- "Bumps"
pdat.b8$simulation <- "Bumps"
pdat.b128$simulation <- "Bumps"
pdat.b1$intensity <- "(1/100, 3)"
pdat.b8$intensity <- "(1/8, 8)"
pdat.b128$intensity <- "(1/128, 128)"
pdat <- rbind(pdat.s1,pdat.s8,pdat.s128,
pdat.ang1,pdat.ang8,pdat.ang128,
pdat.hs1,pdat.hs8,pdat.hs128,
pdat.bur1,pdat.bur8,pdat.bur128,
pdat.cb1,pdat.cb8,pdat.cb128)
pA <- create.bar.plots(pdat,show.legend = FALSE)
pdat <- rbind(pdat.b1,pdat.b8,pdat.b128)
pB <- create.bar.plots(pdat)
plot_grid(pA,pB,nrow = 1,rel_widths = c(7,4))
sessionInfo()
# R version 3.6.2 (2019-12-12)
# Platform: x86_64-apple-darwin15.6.0 (64-bit)
# Running under: macOS Catalina 10.15.5
#
# Matrix products: default
# BLAS: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
# LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
#
# Random number generation:
# RNG: Mersenne-Twister
# Normal: Inversion
# Sample: Rounding
#
# locale:
# [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#
# attached base packages:
# [1] stats graphics grDevices utils datasets methods base
#
# other attached packages:
# [1] cowplot_1.0.0 ggplot2_3.3.0 kableExtra_1.1.0 knitr_1.26
# [5] plyr_1.8.5 haarfisz_4.5 wavethresh_4.6.8 MASS_7.3-51.4
# [9] smashr_1.2-5
#
# loaded via a namespace (and not attached):
# [1] Rcpp_1.0.3 invgamma_1.1 lattice_0.20-38 assertthat_0.2.1
# [5] zeallot_0.1.0 rprojroot_1.3-2 digest_0.6.23 truncnorm_1.0-8
# [9] R6_2.4.1 backports_1.1.5 evaluate_0.14 highr_0.8
# [13] httr_1.4.1 pillar_1.4.3 rlang_0.4.5 rstudioapi_0.10
# [17] data.table_1.12.8 irlba_2.3.3 whisker_0.4 Matrix_1.2-18
# [21] rmarkdown_2.0 labeling_0.3 webshot_0.5.2 readr_1.3.1
# [25] stringr_1.4.0 munsell_0.5.0 mixsqp_0.3-44 compiler_3.6.2
# [29] httpuv_1.5.2 xfun_0.11 pkgconfig_2.0.3 SQUAREM_2017.10-1
# [33] htmltools_0.4.0 tidyselect_0.2.5 tibble_2.1.3 workflowr_1.6.2
# [37] viridisLite_0.3.0 crayon_1.3.4 dplyr_0.8.3 withr_2.1.2
# [41] later_1.0.0 bitops_1.0-6 grid_3.6.2 gtable_0.3.0
# [45] lifecycle_0.1.0 git2r_0.26.1 magrittr_1.5 scales_1.1.0
# [49] stringi_1.4.3 farver_2.0.1 fs_1.3.1 promises_1.1.0
# [53] xml2_1.2.2 vctrs_0.2.1 tools_3.6.2 glue_1.3.1
# [57] purrr_0.3.3 hms_0.5.2 yaml_2.2.0 colorspace_1.4-1
# [61] ashr_2.2-50 caTools_<IP_ADDRESS> rvest_0.3.5


welcome to
the best place to explore and interact with thousands of cutting edge ideas, projects and products


{% extends "layout.html" %} {% block page_title %} GOV.UK prototype kit {% endblock %} {% block content %}
ALPHA This is a new service – your feedback will help us to improve it.
See how people are accessing services, how many transactions are happening, and the ways services may be creating extra effort for their users.
Or view summary


 Mary, sadly missed by her loving family, husband Paddy, daughter Helen (O’Shea), sons Michael, Niall, Ian and Pearse, grandchildren Amy, Colin, Hazel, Alison, Ronan and Daire, brothers Mick and Tommy, son-in-law, daughters-in-law, sisters-in-law, brother-in-law, nephews, nieces, kind neighbours and friends. Reposing at Whelan’s Funeral Home, Bansha Road, Tipperary, on Tuesday evening from 5.30pm with removal at 7.30pm to St. Michael’s Church. Requiem Mass on Wednesday morning at 10.30am and funeral afterwards to St. Michael’s Cemetery, Tipperary.
The late Christy Scott
The death has occurred of Christy Scott late of Egmont View, Mallow, Cork / Mullinahone, Tipperary. Peacefully, at Marymount Hospice, Cork, BQMS. Christy (retired 4th Battalion Collins Barrack, Cork). Beloved husband of Eileen (nee Murphy) and much loved father of Linda (Fitzgibbon) and Christopher, brother of Johny and Willie, son-in-law Thomas, daughter-in-law Marie, grandchildren Lauren, Alex, Robyn, Jack, Scott, Laya and CJ, brother-in-law, sisters-in-law, extended family, nephews, nieces, relatives and friends. Reposing in O'Keeffe's Funeral Home, Bank Place, Buttevant. Rosary on Monday 18th November at 7pm. Reposing in O'Keeffe's Funeral Home on Tuesday fron 5.30pm to 7.30pm followed by removal to St Nicholas' Church, Churchtown. Requiem Mass on Wednesday at 12.30pm, funeral afterwards to the local cemetery.
To read more deaths in Tipperary click here.


Id: 276
Name: Rat Boss
Status: Dead
Species: Animal
Type: Rat
Gender: unknown
OriginName: Earth (Replacement Dimension)
OriginUrl: https://rickandmortyapi.com/api/location/20
LocationName: Earth (Replacement Dimension)
LocationUrl: https://rickandmortyapi.com/api/location/20
Image: https://rickandmortyapi.com/api/character/avatar/276.jpeg
Episode: ['https://rickandmortyapi.com/api/episode/24']
Url: https://rickandmortyapi.com/api/character/276
Created: 2017-12-31T14:17:21.782Z


Copyright (c) 2017 tduva
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in
compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is
distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
implied. See the License for the specific language governing permissions and limitations under the
License.
Using Material Design icons (https://material.io/icons/), including some modified versions (see in source files), licensed under the Apache License Version 2.0 (Web).
Check out the GitHub Repository for this app for the source code and more information.


{% extends "sixth_app/base.html" %} {% block title %}School DeleteView{% endblock %} {% block body %}
Cancel


BLUEASY
Home
Services
Features
Portfolio
Contact
"I'M am be crazy.
I'M LOOKING FOR THINGS I'VE NEVER SEEN BEFORE."


EXPERIMENTAL implementation of a 3.0 syntax parser. Note that this does NOT reflect any official standard and is likely to change.


--- layout: default title: subtitle: title_tag: Continuous Deployment Software | Continuous Integration Tool | Go CD meta_tag_description: Go continuous deployment, continuous integration and automated testing allow software to be developed to a high standard, easily packaged and deployed to test environments meta_tag_keywords: continuous deployment software, continuous integration tools, automated deployment software, automated testing, go ---
ThoughtWorks offers commercial support for GoCD. Try it out for free if you want some extra help from the original creators of GoCD.
Fill out the form below for a free 30 day trial of GoCD
A huge part of GoCD’s success as an OSS product has been the support of a very active community. We encourage you to join in the discussions to both learn and contribute.


Encoder configuration structure. More...
#include <vpx_encoder.h>
Data Fields | |
| unsigned int | g_usage |
| Algorithm specific "usage" value. | |
| unsigned int | g_threads |
| Maximum number of threads to use. | |
| unsigned int | g_profile |
| Bitstream profile to use. | |
| unsigned int | g_w |
| Width of the frame. | |
| unsigned int | g_h |
| Height of the frame. | |
| struct vpx_rational | g_timebase |
| Stream timebase units. | |
| unsigned int | g_error_resilient |
| Enable error resilient mode. | |
| enum vpx_enc_pass | g_pass |
| Multi-pass Encoding Mode. | |
| unsigned int | g_lag_in_frames |
| Allow lagged encoding. | |
| unsigned int | rc_dropframe_thresh |
| Temporal resampling configuration, if supported by the codec. | |
| unsigned int | rc_resize_allowed |
| Enable/disable spatial resampling, if supported by the codec. | |
| unsigned int | rc_resize_up_thresh |
| Spatial resampling up watermark. | |
| unsigned int | rc_resize_down_thresh |
| Spatial resampling down watermark. | |
| enum vpx_rc_mode | rc_end_usage |
| Rate control algorithm to use. | |
| struct vpx_fixed_buf | rc_twopass_stats_in |
| Two-pass stats buffer. | |
| unsigned int | rc_target_bitrate |
| Target data rate. | |
| unsigned int | rc_min_quantizer |
| Minimum (Best Quality) Quantizer. | |
| unsigned int | rc_max_quantizer |
| Maximum (Worst Quality) Quantizer. | |
| unsigned int | rc_undershoot_pct |
| Rate control undershoot tolerance. | |
| unsigned int | rc_overshoot_pct |
| Rate control overshoot tolerance. | |
| unsigned int | rc_buf_sz |
| Decoder Buffer Size. | |
| unsigned int | rc_buf_initial_sz |
| Decoder Buffer Initial Size. | |
| unsigned int | rc_buf_optimal_sz |
| Decoder Buffer Optimal Size. | |
| unsigned int | rc_2pass_vbr_bias_pct |
| Two-pass mode CBR/VBR bias. | |
| unsigned int | rc_2pass_vbr_minsection_pct |
| Two-pass mode per-GOP minimum bitrate. | |
| unsigned int | rc_2pass_vbr_maxsection_pct |
| Two-pass mode per-GOP maximum bitrate. | |
| enum vpx_kf_mode | kf_mode |
| Keyframe placement mode. | |
| unsigned int | kf_min_dist |
| Keyframe minimum interval. | |
| unsigned int | kf_max_dist |
| Keyframe maximum interval. |
Encoder configuration structure.
This structure contains the encoder settings that have common representations across all codecs. This doesn't imply that all codecs support all features, however.
| unsigned int vpx_codec_enc_cfg::g_usage |
Algorithm specific "usage" value.
Algorithms may define multiple values for usage, which may convey the intent of how the application intends to use the stream. If this value is non-zero, consult the documentation for the codec to determine its meaning.
| unsigned int vpx_codec_enc_cfg::g_threads |
Maximum number of threads to use.
For multi-threaded implementations, use no more than this number of threads. The codec may use fewer threads than allowed. The value 0 is equivalent to the value 1.
| unsigned int vpx_codec_enc_cfg::g_profile |
Bitstream profile to use.
Some codecs support a notion of multiple bitstream profiles. Typically this maps to a set of features that are turned on or off. Often the profile to use is determined by the features of the intended decoder. Consult the documentation for the codec to determine the valid values for this parameter, or set to zero for a sane default. profile of bitstream to use
| unsigned int vpx_codec_enc_cfg::g_w |
Width of the frame.
This value identifies the presentation resolution of the frame, in pixels. Note that the frames passed as input to the encoder must have this resolution. Frames will be presented by the decoder in this resolution, independent of any spatial resampling the encoder may do.
| unsigned int vpx_codec_enc_cfg::g_h |
Height of the frame.
This value identifies the presentation resolution of the frame, in pixels. Note that the frames passed as input to the encoder must have this resolution. Frames will be presented by the decoder in this resolution, independent of any spatial resampling the encoder may do.
struct vpx_rational vpx_codec_enc_cfg::g_timebase [read] |
Stream timebase units.
Indicates the smallest interval of time, in seconds, used by the stream. For fixed frame rate material, or variable frame rate material where frames are timed at a multiple of a given clock (ex: video capture), the RECOMMENDED method is to set the timebase to the reciprocal of the frame rate (ex: 1001/30000 for 29.970 Hz NTSC). This allows the pts to correspond to the frame number, which can be handy. For re-encoding video from containers with absolute time timestamps, the RECOMMENDED method is to set the timebase to that of the parent container or multimedia framework (ex: 1/1000 for ms, as in FLV).
| unsigned int vpx_codec_enc_cfg::g_error_resilient |
Enable error resilient mode.
Error resilient mode indicates to the encoder that it should take measures appropriate for streaming over lossy or noisy links, if possible. Set to 1 to enable this feature, 0 to disable it.
Multi-pass Encoding Mode.
This value should be set to the current phase for multi-pass encoding. For single pass, set to VPX_RC_ONE_PASS.
| unsigned int vpx_codec_enc_cfg::g_lag_in_frames |
Allow lagged encoding.
If set, this value allows the encoder to consume a number of input frames before producing output frames. This allows the encoder to base decisions for the current frame on future frames. This does increase the latency of the encoding pipeline, so it is not appropriate in all situations (ex: realtime encoding).
Note that this is a maximum value -- the encoder may produce frames sooner than the given limit. Set this value to 0 to disable this feature.
| unsigned int vpx_codec_enc_cfg::rc_dropframe_thresh |
Temporal resampling configuration, if supported by the codec.
Temporal resampling allows the codec to "drop" frames as a strategy to meet its target data rate. This can cause temporal discontinuities in the encoded video, which may appear as stuttering during playback. This trade-off is often acceptable, but for many applications is not. It can be disabled in these cases.
Note that not all codecs support this feature. All vpx VPx codecs do. For other codecs, consult the documentation for that algorithm.
This threshold is described as a percentage of the target data buffer. When the data buffer falls below this percentage of fullness, a dropped frame is indicated. Set the threshold to zero (0) to disable this feature.
| unsigned int vpx_codec_enc_cfg::rc_resize_allowed |
Enable/disable spatial resampling, if supported by the codec.
Spatial resampling allows the codec to compress a lower resolution version of the frame, which is then upscaled by the encoder to the correct presentation resolution. This increases visual quality at low data rates, at the expense of CPU time on the encoder/decoder.
| unsigned int vpx_codec_enc_cfg::rc_resize_up_thresh |
Spatial resampling up watermark.
This threshold is described as a percentage of the target data buffer. When the data buffer rises above this percentage of fullness, the encoder will step up to a higher resolution version of the frame.
| unsigned int vpx_codec_enc_cfg::rc_resize_down_thresh |
Spatial resampling down watermark.
This threshold is described as a percentage of the target data buffer. When the data buffer falls below this percentage of fullness, the encoder will step down to a lower resolution version of the frame.
Rate control algorithm to use.
Indicates whether the end usage of this stream is to be streamed over a bandwidth constrained link, indicating that Constant Bit Rate (CBR) mode should be used, or whether it will be played back on a high bandwidth link, as from a local disk, where higher variations in bitrate are acceptable.
struct vpx_fixed_buf vpx_codec_enc_cfg::rc_twopass_stats_in [read] |
Two-pass stats buffer.
A buffer containing all of the stats packets produced in the first pass, concatenated.
| unsigned int vpx_codec_enc_cfg::rc_target_bitrate |
Target data rate.
Target bandwidth to use for this stream, in kilobits per second.
| unsigned int vpx_codec_enc_cfg::rc_min_quantizer |
Minimum (Best Quality) Quantizer.
The quantizer is the most direct control over the quality of the encoded image. The range of valid values for the quantizer is codec specific. Consult the documentation for the codec to determine the values to use. To determine the range programmatically, call vpx_codec_enc_config_default() with a usage value of 0.
| unsigned int vpx_codec_enc_cfg::rc_max_quantizer |
Maximum (Worst Quality) Quantizer.
The quantizer is the most direct control over the quality of the encoded image. The range of valid values for the quantizer is codec specific. Consult the documentation for the codec to determine the values to use. To determine the range programmatically, call vpx_codec_enc_config_default() with a usage value of 0.
| unsigned int vpx_codec_enc_cfg::rc_undershoot_pct |
Rate control undershoot tolerance.
This value, expressed as a percentage of the target bitrate, describes the target bitrate for easier frames, allowing bits to be saved for harder frames. Set to zero to use the codec default.
| unsigned int vpx_codec_enc_cfg::rc_overshoot_pct |
Rate control overshoot tolerance.
This value, expressed as a percentage of the target bitrate, describes the maximum allowed bitrate for a given frame. Set to zero to use the codec default.
| unsigned int vpx_codec_enc_cfg::rc_buf_sz |
Decoder Buffer Size.
This value indicates the amount of data that may be buffered by the decoding application. Note that this value is expressed in units of time (milliseconds). For example, a value of 5000 indicates that the client will buffer (at least) 5000ms worth of encoded data. Use the target bitrate (rc_target_bitrate) to convert to bits/bytes, if necessary.
| unsigned int vpx_codec_enc_cfg::rc_buf_initial_sz |
Decoder Buffer Initial Size.
This value indicates the amount of data that will be buffered by the decoding application prior to beginning playback. This value is expressed in units of time (milliseconds). Use the target bitrate (rc_target_bitrate) to convert to bits/bytes, if necessary.
| unsigned int vpx_codec_enc_cfg::rc_buf_optimal_sz |
Decoder Buffer Optimal Size.
This value indicates the amount of data that the encoder should try to maintain in the decoder's buffer. This value is expressed in units of time (milliseconds). Use the target bitrate (rc_target_bitrate) to convert to bits/bytes, if necessary.
| unsigned int vpx_codec_enc_cfg::rc_2pass_vbr_bias_pct |
Two-pass mode CBR/VBR bias.
Bias, expressed on a scale of 0 to 100, for determining target size for the current frame. The value 0 indicates the optimal CBR mode value should be used. The value 100 indicates the optimal VBR mode value should be used. Values in between indicate which way the encoder should "lean." RC mode bias between CBR and VBR(0-100: 0->CBR, 100->VBR)
| unsigned int vpx_codec_enc_cfg::rc_2pass_vbr_minsection_pct |
Two-pass mode per-GOP minimum bitrate.
This value, expressed as a percentage of the target bitrate, indicates the minimum bitrate to be used for a single GOP (aka "section")
| unsigned int vpx_codec_enc_cfg::rc_2pass_vbr_maxsection_pct |
Two-pass mode per-GOP maximum bitrate.
This value, expressed as a percentage of the target bitrate, indicates the maximum bitrate to be used for a single GOP (aka "section")
Keyframe placement mode.
This value indicates whether the encoder should place keyframes at a fixed interval, or determine the optimal placement automatically (as governed by the kf_min_dist and kf_max_dist parameters)
| unsigned int vpx_codec_enc_cfg::kf_min_dist |
Keyframe minimum interval.
This value, expressed as a number of frames, prevents the encoder from placing a keyframe nearer than kf_min_dist to the previous keyframe. At least kf_min_dist frames non-keyframes will be coded before the next keyframe. Set kf_min_dist equal to kf_max_dist for a fixed interval.
| unsigned int vpx_codec_enc_cfg::kf_max_dist |
Keyframe maximum interval.
This value, expressed as a number of frames, forces the encoder to code a keyframe if one has not been coded in the last kf_max_dist frames. A value of 0 implies all frames will be keyframes. Set kf_min_dist equal to kf_max_dist for a fixed interval.


Phone:<PHONE_NUMBER>
Email<EMAIL_ADDRESS>Address: Mayor Street IFSC Dublin 1
please contact us if you would like to know anything about a recipe or anything about or site. We will gladly get back to you.


|
SystemC
2.3.3
Accellera SystemC proof-of-concept library
|
#include <sysc/utils/sc_pvector.h>
Public Types | |
| typedef const T * | const_iterator |
| typedef T * | iterator |
Public Member Functions | |
| sc_pvector (int alloc_n=0) | |
| sc_pvector (const sc_pvector< T > &rhs) | |
| ~sc_pvector () | |
| std::size_t | size () const |
| iterator | begin () |
| const_iterator | begin () const |
| iterator | end () |
| const_iterator | end () const |
| sc_pvector< T > & | operator= (const sc_pvector< T > &rhs) |
| T & | operator[] (unsigned int i) |
| const T & | operator[] (unsigned int i) const |
| T & | fetch (int i) |
| const T & | fetch (int i) const |
| T * | raw_data () |
| const T * | raw_data () const |
| operator const ::std::vector< T > & () const | |
| void | push_back (T item) |
| void | erase_all () |
| void | sort (CFT compar) |
| void | put (T item, int i) |
| void | decr_count () |
| void | decr_count (int k) |
Protected Attributes | |
| mutable ::std::vector< T > | m_vector |
Definition at line 52 of file sc_pvector.h.
| typedef const T* sc_core::sc_pvector< T >::const_iterator |
Definition at line 56 of file sc_pvector.h.
| typedef T* sc_core::sc_pvector< T >::iterator |
Definition at line 57 of file sc_pvector.h.
|
inline |
Definition at line 61 of file sc_pvector.h.
|
inline |
Definition at line 65 of file sc_pvector.h.
|
inline |
Definition at line 69 of file sc_pvector.h.
|
inline |
Definition at line 77 of file sc_pvector.h.
|
inline |
Definition at line 80 of file sc_pvector.h.
|
inline |
Definition at line 140 of file sc_pvector.h.
|
inline |
Definition at line 143 of file sc_pvector.h.
|
inline |
Definition at line 83 of file sc_pvector.h.
|
inline |
Definition at line 86 of file sc_pvector.h.
|
inline |
Definition at line 129 of file sc_pvector.h.
|
inline |
Definition at line 108 of file sc_pvector.h.
|
inline |
Definition at line 111 of file sc_pvector.h.
|
inline |
Definition at line 122 of file sc_pvector.h.
|
inline |
Definition at line 92 of file sc_pvector.h.
|
inline |
Definition at line 96 of file sc_pvector.h.
|
inline |
Definition at line 102 of file sc_pvector.h.
|
inline |
Definition at line 125 of file sc_pvector.h.
|
inline |
Definition at line 137 of file sc_pvector.h.
|
inline |
Definition at line 115 of file sc_pvector.h.
|
inline |
Definition at line 118 of file sc_pvector.h.
|
inline |
Definition at line 73 of file sc_pvector.h.
|
inline |
Definition at line 132 of file sc_pvector.h.
|
protected |
Definition at line 149 of file sc_pvector.h.


UFC Sao Paulo results: Shogun Rua and Paul Craig fight to a split draw
by Eddie MercadoThe UFC Sao Paulo co-main event just closed out with UFC Hall of Famer, Shogun Rua, fighting to a split draw with Paul Craig. Shogun rallied after a rough opening round, and is currently the promotion’s #14 ranked light heavyweight. As for Craig, this is the best he’s ever looked on his feet.
Craig started hot, throwing an assortment of kicks and backing up the veteran. They spent a lot of time in the clinch, but there was a moment where Craig broke apart and just started throwing all the punches. Shogun weathered the storm and landed a few solo strikes here and there, but the opening act was all Craig.
The second round was completely different than the opening act. Shogun came out and scored a takedown and landed some quality ground strikes. He would stand up above Craig and dive in with a big punch. He did this several times. Craig did not return to his feet that round.
Craig ended up on his back again in the final round after flopping to his back from botching a takedown. He struggled to sweep and lock up a submission attempt. Shogun went back to standing up and diving in with a punch. Craig finally stood to his feet but ate a hard two-piece from Shogun. Craig blasted a takedown to end the round on top.


d) Write a JS function that will add a row to HTML table based on contents of a form on the same page. Function should be invoked using HTML button.


Your Online Learning Resources
{% for i in o %}
Youtube results
{{i}}
Google Results !
{{i}}
{%endfor%}


Search Results
Hilton
account_balance_wallet
I am a very simple card. I am good at containing small bits of information. I am convenient because I require little markup to use effectively.
Hilton 2
account_balance_wallet
I am a very simple card. I am good at containing small bits of information. I am convenient because I require little markup to use effectively.
Hilton 3
account_balance_wallet
I am a very simple card. I am good at containing small bits of information. I am convenient because I require little markup to use effectively.


--- layout: page title: 关于我 header: Post Archive group: navigation comments: false ---
{% include JB/setup %}


Birthday names
This form enables you to know your birth name by filling in the required details
Date:
Gender:
Choose Gender
Male
Female
Get A Name


Beachbum Berry’s Total Tiki Online
(for personal computers and mobile)
Total Tiki Online is the definitive reference and electronic tool for classic and contemporary exotic mixed drinks from historian Jeff “Beachbum” Berry!
Features:
- over 250 curated historical exotic drink recipes from Don the Beachcomber, Trader Vic, and many others, including the authoritative recipes for the Zombie, Mai Tai, and Scorpion, and scores of less famous, but brilliant concoctions from the heyday of the 1940s, 1950s and 1960s, as well as standouts from the 1970s–1990s, with more to come
- over 60 delicious contemporary exotic drink recipes carefully selected from the “tiki revival” that began around the year 2000, with more to come
- rare period and contemporary imagery from Beachbum Berry’s collection, with a lot more to come
- the perfect complement to Jeff “Beachbum” Berry’s books, such as Sippin’ Safari, Potions of the Caribbean, Grog Log, and Remixed!
- data rich, with pictures, keywords, flavor clouds, and other data
- unprecedented information management for the exotic drink aficionado:
- smartly your ingredient inventory; you can even have multiple inventories for separate homes, vacations, or for planning events
- find the drinks you can make with the ingredients you have in your inventory
- annotate recipes with your own notes, including what you like and dislike for future reference
- rescale recipes on demand to fit your glassware
- calculate your pour costs
- create handy lists of recipes and ingredients
- calculate your ingredient needs for parties
- enter your own private recipes and enjoy the same data-rich features of our curated content! (may carry additional cost)
- access from any current web browser including your phone
If this sounds good, your next step is to create a free account, log in, and poke around. If you like what you see, the basic subscription costs around US$3/mo (quarterly or annually).
CREATE FREE ACCOUNTBelow are video tutorials for the service that you’re welcome to peruse for a detailed preview of what is offered:


public class ARXCostBenefitConfiguration
extends java.lang.Object
implements java.io.Serializable
| Modifier and Type | Method and Description |
|---|---|
ARXCostBenefitConfiguration |
clone() |
static ARXCostBenefitConfiguration |
create()
Creates a new instance
|
double |
getAdversaryCost()
Returns the amount of money needed by an attacker for trying to re-identify a single record
|
double |
getAdversaryGain()
Returns the amount of money earned by an attacker for successfully re-identifying a single record
|
double |
getPublisherBenefit()
Returns the amount of money earned by the data publisher for publishing a single record
|
double |
getPublisherLoss()
Returns the amount of money lost by the data publisher, e.g. due to a fine, if a single record is attacked successfully
|
ARXCostBenefitConfiguration |
setAdversaryCost(double adversaryCost)
Sets the amount of money needed by an attacker for trying to re-identify a single record
|
ARXCostBenefitConfiguration |
setAdversaryGain(double adversaryGain)
Sets the amount of money earned by an attacker for successfully re-identifying a single record
|
ARXCostBenefitConfiguration |
setPublisherBenefit(double publisherBenefit)
Sets the amount of money earned by the data publisher for publishing a single record
|
ARXCostBenefitConfiguration |
setPublisherLoss(double publisherLoss)
Sets the amount of money lost by the data publisher, e.g. due to a fine, if a single record is attacked successfully
|
java.lang.String |
toString() |
public static ARXCostBenefitConfiguration create()
public ARXCostBenefitConfiguration clone()
clone
in class java.lang.Object
public double getAdversaryCost()
public double getAdversaryGain()
public double getPublisherBenefit()
public double getPublisherLoss()
public ARXCostBenefitConfiguration setAdversaryCost(double adversaryCost)
adversaryCost
- the adversaryCost to setpublic ARXCostBenefitConfiguration setAdversaryGain(double adversaryGain)
adversaryGain
- the adversaryGain to setpublic ARXCostBenefitConfiguration setPublisherBenefit(double publisherBenefit)
publisherBenefit
- the publisherBenefit to setpublic ARXCostBenefitConfiguration setPublisherLoss(double publisherLoss)
publisherLoss
- the publisherLoss to setpublic java.lang.String toString()
toString
in class java.lang.Object


Colors
Hunter Green
#3D5A42
#3D5A42
Olive
#A4A65F
#A4A65F
Brown Green
#8E8454
#8E8454
Mocha
#5A5444
#5A5444
Brown Grey
#746C55
#746C55
Fonts
Karla
- The quick brown fox jumps over the lazy dog.
- The quick brown fox jumps over the lazy dog.
- The quick brown fox jumps over the lazy dog.
Oxygen
- The quick brown fox jumps over the lazy dog.
- The quick brown fox jumps over the lazy dog.
- The quick brown fox jumps over the lazy dog.
Quicksand
- The quick brown fox jumps over the lazy dog.
- The quick brown fox jumps over the lazy dog.
- The quick brown fox jumps over the lazy dog.
Text Styles
H1: Main Page Heading
- Font-weight: 700
- Font-size: 28px
- Font-family: Oxygen
Subheading
- Font-weight: 500
- Font-size: 24px
- Font-family: Karla
Paragraph Text
- Font-weight: 400
- Font-size: 18px
- Font-family: Quicksand


Vegeta is one of the last survivors of the saiyan race. Early in the DragonBall Z series he is protrayed as a stubborn, villainous character who will stop at nothing to obtain absolute power. It is only after being humbled by various fighters and Kakorat(Goku) that Vegeta morphs into the anti-hero that he is known for today.


Slider is an input component to provide a numerical input.
Two-way binding is defined using the standard ngModel directive.
Slider can be used in a model driven form as well.
Boundaries are specified with min and max attributes.
Step factor is 1 by default and can be customized with step option.
Range slider provides two handles to define two values. In this case, value binding should refer to an array.
Sliders supports two orientation, horizontal is the default and other alternative is vertical.
| Name | Type | Default | Description |
|---|---|---|---|
| animate | boolean | false | When enabled, displays an animation on click of the slider bar. |
| disabled | boolean | false | When present, it specifies that the element should be disabled. |
| min | number | 0 | Mininum boundary value. |
| max | number | 100 | Maximum boundary value. |
| orientation | string | horizontal | Orientation of the slider, valid values are horizontal and vertical. |
| step | number | 1 | Step factor to increment/decrement the value. |
| range | boolean | false | When specified, allows two boundary values to be picked. |
| style | string | null | Inline style of the component. |
| styleClass | string | null | Style class of the component. |
| tabindex | number | 0 | Index of the element in tabbing order. |
| ariaLabelledBy | string | null | Establishes relationships between the component and label(s) where its value should be one or more element IDs. |
| Name | Parameters | Description |
|---|---|---|
| onChange |
event.originalEvent: Slide event event.value: New value event.values: Values in range mode |
Callback to invoke on value change via slide. |
| onSlideEnd |
event.originalEvent: Mouseup event event.value: New value |
Callback to invoke when slide stops. |
Following is the list of structural style classes, for theming classes visit theming page.
| Name | Element |
|---|---|
| p-slider | Container element |
| p-slider-handle | Handle element |
None.


Emma Watson Says She’s ‘Self-Partnered’, Not Single
by Emily BrownEmma Watson doesn’t see herself as single despite the fact she’s not in a relationship; instead she considers herself ‘self-partnered’.
It’s a good term to use when you’re trying to make yourself feel less guilty about eating both portions of a dessert meant for two – ‘one for me, and one for my partner, me.’
I’ll definitely be adopting it for that exact reason.
The self-partnered way of life would probably prove more problematic when it came to taking part in activities requiring two people, however, like buying a Duo ticket on a train.
But that’s probably not a problem for the Harry Potter star – I can’t imagine Watson needs to scrimp on her train travel.
Anyway, she’s obviously figured out how to deal with all the technicalities that go with being self-partnered, as she’s said she’s ‘very happy’ with her current status.
The 29-year-old spoke about her love life in an interview with Vogue, where she pointed out you don’t need a partner – other than yourself – to feel accomplished as you head into your 30s.
Watson admitted it did take her a while to accept that realisation, however, saying:
I never believed the whole ‘I’m happy single’ spiel. I was like, ‘This is totally spiel.’ It took me a long time, but I’m very happy [being single]. I call it being self-partnered.
With her next big birthday just a few months away, however, Watson did say she’d been feeling anxious about where she was in life.
 This is not a big deal’… Cut to 29, and I’m like, ‘Oh my God, I feel so stressed and anxious.’
 If you have not built a home, if you do not have a husband, if you do not have a baby, and you are turning 30, and you’re not in some incredibly secure, stable place in your career, or you’re still figuring things out…
There’s just this incredible amount of anxiety.
While she might not have a husband or baby, there’s no doubt the actor has accomplished an incredible amount in her 29 years. After making a name for herself on Harry Potter she went on to create other films like The Perks Of Being A Wallflower and the upcoming Little Women.
Watson is also a keen activist who was appointed UN Women Goodwill Ambassador in July 2014 before going on to serve as an advocate for UN Women’s HeForShe campaign in promoting gender equality.
She has also been involved in the promotion of girls’ education as well as fair trade and organic clothing, and earlier this year Watson helped launch a free legal advice helpline for women who have experienced sexual harassment at work.
Many social media users have praised the way Watson spoke about her relationship status, with a few saying they plan to adopt the term ‘self-partnered’ for themselves.
Emily Brown first began delivering important news stories aged just 13, when she launched her career with a paper round. She graduated with a BA Hons in English Language in the Media from Lancaster University, and went on to become a freelance writer and blogger. Emily contributed to The Sunday Times Travel Magazine and Student Problems before becoming a journalist at UNILAD, where she works on breaking news as well as longer form features.


Bears Insider Has Encouraging Update On QB Mitch Trubisky
by Chris RosvoglouEven though Mitch Trubisky suffered a hip injury in Week 11, the third-year quarterback for the Chicago Bears is ready to play this weekend.
Trubisky was pulled out of the game in the fourth quarter last Sunday for Chase Daniel. Head coach Matt Nagy said he made the switch because the former first-round pick was dealing with a hip pointer.
Several fans were questioning the legitimacy of Trubisky’s injury, especially since he’s struggled this season. Well, the latest report from the Bears will most likely add fuel to their argument.
It turns out that Trubisky was a full participant at practice for the third-straight day, per NBC’s JJ Stankevitz.
The expectation in Chicago is that Trubisky will start this weekend against the New York Giants.
He’s not even listed as questionable on the team’s final injury report.
If Trubisky’s injury resurfaces on Sunday, the Bears could bench him. They could also bench him if he struggles to perform against an abysmal Giants defense.
The Bears are having a disappointing season in large part because of their inability to score points on a consistent basis.
Not only does Trubisky need to play well to keep his team’s playoff hopes alive, he’ll have to prove to the coaching staff that he can be the starting quarterback in 2020.
We’ll see if Trubisky can bounce back this Sunday.


This course introduces students to the world of internet and networked systems development. Concepts related to distributed systems development; concurrent and asynchronous processing; process communications and network transport protocols; distributed application architecture and design; deployment, monitoring and debugging of internet-based systems; and web of things development will be covered.
Prerequisites include COSC A212 Introduction to Programming II and Sophomore standing, or Instructor Approval.
To be successful in this course, you should have practical experience building software, and in particular, should be comfortable working with data structures, designing classes, and writing software modules.
The general syllabus describes the common elements of this course across sections and semester offerings.